Many organizations and people store data in tabular format, such as in spreadsheets and databases. The data often represents real-world entities (people, places, things), facts about these entities, and relationships between the entities. While the facts and relationships may be intuitive to a human viewing the data, the system itself lacks knowledge of this information. Software systems that use or manage knowledge may use a data graph to represent real-world entities and relationships between entities to represent facts about the entities. The data graph may provide the semantic structure that allows a system to interpret data and acquire factual knowledge. Data graphs can allow a system to automatically relate and integrate new information with what is already known, easily aggregate and categorize information, and discover relationships. Such capabilities offer a more flexible and complete picture of the data. Because of this, knowledge-based systems often rely on data graphs. But building data graphs, including translating tabular data to a data graph format, has generally been the domain of technical users, e.g., individuals with a programming or information technology background, limiting the use of knowledge-based systems by conventional computer users.